EFFICIENT ATTACKS ON HOMOPHONIC SUBSTITUTION CIPHERS

Substitution ciphers are one of the earliest types of ciphers. Examples of classic substitution ciphers include the well-known simple substitution and the less well-known homophonic substitution. Although simple substitution ciphers are indeed simple - both in terms of their use and attacks; the homophonic substitution ciphers are far more challenging to break. Even with modern computing technology, homophonic substitution ciphers remain a significant challenge. This project focuses on designing, implementing, and testing an efficient attack on homophonic substitution ciphers. We use an iterative approach that generalizes the fastest known attack on simple substitution ciphers and also employs a heuristic search technique for improved efficiency. We test our algorithm on a wide variety of homophonic substitution ciphers. Finally, we apply our technique to the “Zodiac 340” cipher, which is an unsolved ciphertext created in the 1970s by the infamous Zodiac killer

Cryptanalysis of Homophonic Substitution-Transposition Cipher

Homophonic substitution ciphers employ a one-to-many key to encrypt plaintext. This is in contrast to a simple substitution cipher where a one-to-one mapping is used. The advantage of a homophonic substitution cipher is that it makes frequency analysis more difficult, due to a more even distribution of plaintext statistics. Classic transposition ciphers apply diffusion to the ciphertext by swapping the order of letters. Combined transposition-substitution ciphers can be more challenging to cryptanalyze than either cipher type separately. In this research, we propose a technique to break a combined simple substitution- column transposition cipher. We also consider the related problem of breaking a combination homophonic substitution-column transposition cipher. These attacks extend previous work on substitution ciphers. We thoroughly analyze our attacks and we apply the homophonic substitution-columnar transposition attack to the unsolved Zodiac-340 cipher

Heuristic Search Cryptanalysis of the Zodiac 340 Cipher

The Zodiac 340 cipher is one of the most famous unsolved ciphers of all time. It was allegedly written by “the Zodiac”, whose identity remains unknown to date. The Zodiac was a serial killer who killed a number of people in and around the San Francisco Bay area during the 1960s. He is confirmed to have seven victims, two of whom survived [1], although in taunting letters to the news media he claims to have killed 37 people. During this time, an encrypted message known as the Zodiac 408 cipher was mailed to 3 different newspapers in the San Francisco bay area. This was a homophonic cipher and was successfully decoded. Within a few days he sent out another cipher that was 340 characters long [4]. This cipher, which is known as the Zodiac 340 cipher, is unsolved to date. Many cryptologists have tried to crack this cipher but with no success. In this project, we implemented a novel genetic algorithm in an attempt to crack the Zodiac 340 cipher. We have attacked the cipher as a homophonic cipher where each cipher symbol is mapped to only a single English letter, but each English letter can be mapped to multiple cipher symbols. In the genetic algorithm, we implemented two variants of crossover: simple and intelligent. The simple crossover looks for commonly occurring substrings, without looking for actual English words in a putative decrypt. The intelligent crossover counts the number of actual English words that can be found in a putative decrypt when evaluating each solution. We implemented a dictionary lookup for quickly identifying English words for the intelligent crossover. The genetic algorithm using a combination of simple and intelligent crossovers was able to identify many English words in various putative decrypts but no solution was found

Cryptanalysis of Classic Ciphers Using Hidden Markov Models

Cryptanalysis is the study of identifying weaknesses in the implementation of cryptographic algorithms. This process would improve the complexity of such algo- rithms, making the system secure. In this research, we apply Hidden Markov Models (HMMs) to classic cryptanaly- sis problems. We show that with sufficient ciphertext, an HMM can be used to break a simple substitution cipher. We also show that when limited ciphertext is avail- able, using multiple random restarts for the HMM increases our chance of successful decryption

Cryptanalysis of Homophonic Substitution Cipher Using Hidden Markov Models

We investigate the effectiveness of a Hidden Markov Model (HMM) with random restarts as a mean of breaking a homophonic substitution cipher. Based on extensive experiments, we find that such an HMM-based attack outperforms a previously de- veloped nested hill climb approach, particularly when the ciphertext message is short. We then consider a combination cipher, consisting of a homophonic substitution and a column transposition. We develop and analyze an attack on such a cipher. This attack employs an HMM (with random restarts), together with a hill climb to recover the column permutation. We show that this attack can succeed on relatively short ci- phertext messages. Finally, we test this combined attack on the unsolved Zodiac 340 cipher

Real Life Cryptology

A large number of enciphered documents survived from early modern Hungary. This area was a particularly fertile territory where cryptographic methods proliferated, because a large portion of the population was living in the frontier zone, and participated (or was forced to participate) in the network of the information flow. A quantitative analysis of sixteenth-century to seventeenth-century Hungarian ciphers (300 cipher keys and 1,600 partly or entirely enciphered letters) reveals that besides the dominance of diplomatic use of cryptography, there were many examples of “private” applications too. This book reconstructs the main reasons and goals why historical actors chose to use ciphers in a diplomatic letter, a military order, a diary or a private letter, what they decided to encrypt, and how they perceived the dangers threatening their messages

Generative Adversarial Networks for Classic Cryptanalysis

The necessity of protecting critical information has been understood for millennia. Although classic ciphers have inherent weaknesses in comparison to modern ciphers, many classic ciphers are extremely challenging to break in practice. Machine learning techniques, such as hidden Markov models (HMM), have recently been applied with success to various classic cryptanalysis problems. In this research, we consider the effectiveness of the deep learning technique CipherGAN---which is based on the well- established generative adversarial network (GAN) architecture---for classic cipher cryptanalysis. We experiment extensively with CipherGAN on a number of classic ciphers, and we compare our results to those obtained using HMMs